WO2014060555A1 - Gene signatures of inflammatory disorders that relate to the liver - Google Patents

Gene signatures of inflammatory disorders that relate to the liver Download PDF

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Publication number
WO2014060555A1
WO2014060555A1 PCT/EP2013/071793 EP2013071793W WO2014060555A1 WO 2014060555 A1 WO2014060555 A1 WO 2014060555A1 EP 2013071793 W EP2013071793 W EP 2013071793W WO 2014060555 A1 WO2014060555 A1 WO 2014060555A1
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seq
genes
chosen
gene
group
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PCT/EP2013/071793
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English (en)
French (fr)
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Matthieu PICHAUD
Pierre Rimbaud
Stanislav Ehrlich
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Enterome
Institut National De La Recherche Agronomique
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Priority to BR112015008621-7A priority Critical patent/BR112015008621A2/pt
Priority to NZ707035A priority patent/NZ707035A/en
Application filed by Enterome, Institut National De La Recherche Agronomique filed Critical Enterome
Priority to AU2013333882A priority patent/AU2013333882B2/en
Priority to IN3796DEN2015 priority patent/IN2015DN03796A/en
Priority to CA2886748A priority patent/CA2886748A1/en
Priority to MX2015004844A priority patent/MX2015004844A/es
Priority to ES13779214T priority patent/ES2821383T3/es
Priority to JP2015537267A priority patent/JP6752016B2/ja
Priority to CN201380054047.XA priority patent/CN104769132B/zh
Priority to DK13779214.9T priority patent/DK2909334T3/da
Priority to EP13779214.9A priority patent/EP2909334B1/de
Priority to US14/435,750 priority patent/US10036074B2/en
Publication of WO2014060555A1 publication Critical patent/WO2014060555A1/en
Priority to IL238025A priority patent/IL238025B/en
Priority to US15/972,620 priority patent/US10626471B2/en
Priority to AU2019210666A priority patent/AU2019210666A1/en

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6888—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms
    • C12Q1/689—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for bacteria
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/16—Primer sets for multiplex assays

Definitions

  • This invention is related to the area of characterization of inflammation in relation with the gut microbiota, in metabolic and autoimmune disorders.
  • it relates to the identification of gene signatures which can be used as a marker predictive of inflammation associated diseases, such as liver-related metabolic disorders, in particular to the evolution of benign steatosis towards its most severe forms (steatohepatitis and cirrhosis) or autoimmune disorders, in particular inflammatory bowel diseases (Crohn's and Ulcerative Colitis).
  • These gene signatures can therefore be used as a means of diagnosis, prognosis, stratification for drug studies, for monitoring patient and for assigning an appropriate treatment.
  • BACKGROUND OF THE INVENTION Systemic and local inflammation is a pathological feature observed in many disorders, and in particular metabolic disorders and autoimmune disorders.
  • Low-grade inflammation is an independent risk factor of metabolic diseases and associated co-morbidities such as heart disease, stroke and diabetes. Inflammation predates the detection of insulin resistance and therefore may be a good predictor of diabetes.
  • Chronic (persistent low-grade) and acute (high-grade) inflammation is a key characteristic feature of autoimmune disorders, such as inflammatory bowel disease.
  • Metabolic syndrome is also known as Syndrome X, metabolic syndrome X, cardiometabolic syndrome, insulin resistance syndrome, CHAOS or Reaven's syndrome. It is generally believed to be a combination of disorders that affect a large number of people in a clustered fashion.
  • the symptoms and features of the syndrome include at least three of the following conditions: diabetes mellitus II, impaired glucose tolerance or insulin resistance, high blood pressure, central obesity and difficulty in losing weight, high cholesterol, combined hyperlipidemia, and fatty liver. On a physiological basis, insulin resistance appears to be responsible for the syndrome.
  • insulin resistance can be defined in a myriad of different ways, including impaired glucose metabolism, inability to suppress lipolysis in the tissues, defective protein synthesis, altered cell differentiation, abnormal cell cycle control or proliferation, all of which being implicated in the liver and cardiovascular disease associated with metabolic syndrome.
  • Nonalcoholic fatty liver disease NAFLD is the hepatic manifestation of the metabolic syndrome, with insulin resistance as the main pathogenetic mechanism.
  • Non-alcoholic fatty liver disease (NAFLD) represents a spectrum of liver diseases encompassing simple fatty infiltration in liver tissue (steatosis), fat and inflammation of the liver tissue (non-alcoholic steatohepatitis - NASH), and cirrhosis, in the absence of excessive alcohol consumption, viral diseases (HCV, HBV) or other identified etiologies (autoimmune disorders). It is the leading cause of chronic liver diseases in Western countries with a prevalence as high as 30% of the general population. Concerning NASH, studies reported an estimated prevalence of 3 to 5% of the general population.
  • NAFLD is strongly associated with obesity (NAFLD found in more than 90% of obese patients), type 2 diabetes (NAFLD is found in 40% to 70% of T2D patients), and dyslipidaemia. NAFLD may thus be considered as the hepatic manifestation of the metabolic syndrome.
  • NASH is considered as the second most frequent etiology for liver transplant indication, after HCV, representing 18% of patients registered in US transplants list (OPTN).
  • liver biopsy is currently considered as the best tool for assessing degree of severity of the NAFLD, and in particular inflammation and of liver fibrosis.
  • liver biopsy is an invasive procedure which is not appropriate or practical outside specialist hepatology practice.
  • it presents drawbacks of interpretation error due to sampling error and to observer variability (Adams LA. & Feldstein A.E., Journal of Digestive Diseases 2011).
  • NAFLD is often asymptomatic and commonly first discovered as an incidental biochemical abnormality identified during routine blood tests.
  • the characteristic biochemical changes e.g., a relatively greater rise in alanine aminotransferase than in aspartate aminotransferase
  • alanine aminotransferase levels fall as hepatic fibrosis progresses. This means that steatohepatitis with advanced disease may be present even in those with relatively normal alanine aminotransferase levels in blood.
  • NAFLD Non Alcoholic Fatty Liver Disease
  • the present Inventors identified particular gene signatures which are predictive of the evolution of Non Alcoholic Fatty Liver Disease (NAFLD) towards its most severe forms (hepatitis, cirrhosis, liver cancer). These gene signatures are advantageously assessed in stool samples of the patients. These gene signatures are therefore considered to be the first reliable and non-invasive means of diagnosis, prognosis, and stratification for drug studies of liver-related metabolic diseases. They can also be used for monitoring and assigning appropriate treatments to the thus-diagnosed patients.
  • NAFLD Non Alcoholic Fatty Liver Disease
  • IBD Inflammatory bowel diseases
  • Crohn's disease or ulcerative colitis are among the most prevalent autoimmune disorders.
  • 3 main approaches Clinical evaluation, mainly using composite scores that integrate both patients data as well as patients self-report questionnaires;
  • Biological markers based on blood (ie inflammation markers such as C P, or platelet count), or feces (ie calprotectin); and
  • - Imaging tools including endoscopic exams with or without histologic analysis and magnetic resonance based exams (MRI or MR enterography).
  • stable patients are defined as patients for whom disease activity is stable over several weeks (patient in a "stable state”). While instable patients (or patient “in an instable state”) are patients: who had their treatment changed or intensified in the following weeks,
  • Figure 5 discloses the low or high relative abundance of the genes of the two clusters 1 and 31 for the NASHl cohort (A), the NASH2 cohort (B), and the Crohn cohort (C) (circles represent simple steatosis or Crohn-stable status whereas crosses represent NASH or Crohn-instable status).
  • Figure 6 discloses the low or high relative abundance of the genes of the two clusters 1 and 19 for the NASHl cohort (A), the NASH2 cohort (B), and the Crohn cohort (C) (circles represent simple steatosis or Crohn-stable status whereas crosses represent NASH or Crohn-instable status).
  • Figure 7 discloses the low or high relative abundance of the genes of the two clusters 19 and 31 for the NASHl cohort (A), the NASH2 cohort (B), and the Crohn cohort (C) (circles represent simple steatosis or Crohn-stable status whereas crosses represent NASH or Crohn-instable status).
  • the term "inflammatory disease” designates metabolic disorders associated with a systemic change of expression of pro- and anti-inflammatory cytokines.
  • C-reactive protein and adipocytokines i.e. tumor necrosis factor-alpha (TN F-a), interleukin-6 (IL-6), and adiponectin
  • TN F-a tumor necrosis factor-alpha
  • IL-6 interleukin-6
  • adiponectin i.e. tumor necrosis factor-alpha
  • C-reactive protein, fecal calprotectin and cytokines e. tumor necrosis factor-alpha (TNF-a), interleukin-6 (IL-6), interleukin-8 (IL8) have been often observed as the pro- and antiinflammatory cytokines associated with inflammatory bowel diseases.
  • said inflammatory disease is chosen in the group consisting of: insulin resistance, hypercholesterolemia, impaired glucose tolerance, type 2 diabetes, hypertension, cardiovascular diseases, inflammatory bowel diseases, rheumatoid disorders and liver diseases.
  • Liver disease is also referred to as "hepatic disease”. It is a broad term that covers all the potential problems that cause the liver to fail to perform its designated functions. More specifically, it encompasses in the present application all the different stages of liver steatosis, non-alcoholic liver steatohepatitis, liver fibrosis, cirrhosis, liver failure, and liver cancer.
  • NAFLD Nonalcoholic Fatty Liver Disease
  • Stepsis is also often referred to as “non-alcoholic fatty liver” (NAFL). It corresponds to the presence of hepatic steatosis with no evidence of hepatocellular injury in the form of ballooning of the hepatocytes or no evidence of fibrosis. It will be also designated hereafter as “simple steatosis”. On a medical point of view, steatosis occurs through several mechanisms. First, expansion and inflammation of adipose tissue results in adipose insulin resistance and increased lipolysis and thereby in an elevated flux of free fatty acids into the liver.
  • OS reactive oxidative species
  • gut-derived signals e.g., bacterial endotoxins, short-chain fatty acids
  • inflammatory cytokines e.g., IL-12, IL-12, and IL-12.
  • adipokines e.g., IL-12, IL-12, and IL-12.
  • the term "benign steatosis” will be used in the present application to designate a condition in which hepatic steatosis is present, but there is a minimal risk (if any) that this steatosis will progress into steatohepatitis, fibrosis, or cirrhosis.
  • a patient suffering from “benign steatosis” as meant herein is predicted (or prognosed) to have no change in his liver histology parameters.
  • the term "inflammatory steatosis” will be used in the present application to designate a condition in which hepatic steatosis is present, but there is a risk that this steatosis will progress into steatohepatitis, fibrosis, or cirrhosis.
  • a patient suffering from "inflammatory steatosis” as meant herein is predicted (or prognosed) to suffer from a liver steatohepatitis, a liver fibrosis, cirrhosis, liver failure or a liver cancer within the next months or years.
  • Non-alcoholic steatohepatitis is diagnosed in the presence of hepatic steatosis and inflammation with hepatocyte injury (ballooning), with or without fibrosis. This stage can progress to cirrhosis, liver failure and rarely liver cancer.
  • steatohepatitis encompasses non-alcoholic steatohepatitis as well as alcoholic steatohepatitis.
  • NASH cirrhosis is diagnosed in the presence of cirrhosis with current or previous histological evidence of steatosis or steatohepatitis whereas cryptogenic cirrhosis is diagnosed in the presence of cirrhosis with no obvious etiology. Patients with cryptogenic cirrhosis are heavily enriched with metabolic risk factors such as obesity and metabolic syndrome.
  • NASH-associated fibrosis is diagnosed in the presence of hepatic steatosis and inflammation, with fibrosis.
  • Fibrosis corresponds to the formation of excess fibrous connective tissue in a liver in a reparative or reactive process.
  • “Scarring” designates confluent fibrosis that obliterates the architecture of the underlying organ or tissue.
  • Cirrhosis is a consequence of chronic liver disease characterized by replacement of liver tissue by fibrosis, scar tissue and regenerative nodules (lumps that occur as a result of a process in which damaged tissue is regenerated) leading to loss of liver function.
  • Liver failure designates the inability of the liver to perform its normal synthetic and metabolic function as part of normal physiology. Two forms are recognized, acute and chronic. "Acute liver failure” is defined as the rapid development of hepatocellular dysfunction, specifically coagulopathy and mental status changes (encephalopathy) in a patient without known prior liver disease, whereas “chronic liver failure” usually occurs in the context of cirrhosis.
  • Liver cancer designates a malignant tumor that grows on the surface or inside the liver. Liver cancer should not be confused with liver metastases, which are cancers that originate from organs elsewhere in the body and migrate to the liver.
  • Inflammatory bowel diseases herein designates in particular the Crohn disease and ulcerative colitis.
  • inflammatory bowel diseases or rheumatoid disorders belong to "auto-immune disorders”.
  • diagnosis means to identify or to detect that the said subject is actually suffering from said disease or said condition.
  • prognosing a disease or a condition in a subject hereby means to predict that the said subject will suffer from said disease or condition.
  • diagnosis steatosis in a subject means identifying or detecting that said subject has a simple steatosis (and not a NASH).
  • prognosing steatosis in a subject means that said subject actually has a benign steatosis which will remain stable.
  • diagnosing steatohepatitis in a subject means identifying or detecting that said subject suffers from steatohepatitis (with or without fibrosis).
  • prognosing steatohepatitis in a subject means that said subject is likely to develop a steatohepatitis (with or without fibrosis), for example because it has a inflammatory steatosis. In other words, the said subject has a risk of suffering from steatohepatitis (with or without fibrosis).
  • diagnosing fibrosis in a subject means identifying or detecting that said subject suffers from steatohepatitis with fibrosis.
  • prognosing fibrosis in a subject means that said subject is likely to develop a liver fibrosis, for example because it has an inflammatory steatosis or an established steatohepatitis. In other words, the said subject has a risk of suffering from fibrosis.
  • the subject has a risk of suffering from a disease
  • the subject when harbouring gene abundance profiles associated with above-mentioned diseases or conditions has more than 50%, preferably more than 60% and more preferably more than 75% of risk of suffering from the above-mentioned diseases or conditions.
  • the term “metagenome” refers to genomic material obtained directly from a subject, instead of from a cell culture. Metagenome is thus composed of microbial and host components.
  • the term "gene” refers broadly to a genetic information unit. It is composed of DNA or RNA that may code for a polypeptide or for an RNA chain of a given organism. More specifically, a gene is a locatable region of genomic sequence, which is associated with regulatory regions, transcribed regions, and /or other functional sequence regions.
  • the genes which are referred to in this invention are preferably "bacterial genes", i.e., they correspond to a locatable region of the genome of a bacterium.
  • the term “gene signature” refers to a set of information that is related to the amount of one or more gene(s) in a tested sample. This information may arise from the identification of the amount of gene copies or gene products in the tested sample.
  • the “gene signature of the invention” therefore encompasses either the expression level of at least one bacterial gene, preferably of at least two bacterial genes, or the abundance of these at least one or two bacterial genes.
  • the "expression" of a gene is the process by which information from a gene is used in the synthesis of a functional gene product.
  • RNA Ribonucleic acid
  • tRNA transfer RNA
  • snRNA small nuclear RNA
  • Gene expression can thus be detected by determining the presence of the corresponding rRNA, tRNA, mRNA, snRNA and / or the gene products at the protein level, by conventional means.
  • “gene abundance” refers to the absolute or relative amount of the tested genes.
  • “Absolute amount” (or “absolute abundance”) of a gene designates the total number of copies of said gene in a define volume of the tested sample
  • “relative amount” (or “relative abundance”) of a gene designates the total number of copies of said gene relative to the total amount of genes or alternatively the total number of copies of said gene relative to the amount of a single reference gene or preferably a combination of reference genes present in the tested sample.
  • Ubiquitous genes such as genes essential for the survival of the organism like DNA polymerases or genes coding for proteins involved in glucose metabolism, are good candidates for reference genes in metagenomic studies.
  • the "gene signature" used in the method of the invention therefore comprises or consists of either the abundance profile and/or the expression profile (either absolute or relative) of the tested bacterial gene(s).
  • an abundance profile it is meant the absolute or relative abundance of the group of tested genes. This abundance can be determined by detecting the copies number of the tested genes at the DNA level, for example by quantitative PC , sequencing or nucleic acid microarrays.
  • expression profile it is meant the expression levels of the group of tested genes. These expression levels can be determined by detecting the levels of the gene products, for example the transcript levels or the protein levels corresponding to the tested genes.
  • two genes are held “equivalent” if the replacement of one gene by the other in the analyzed gene signature does not significantly affect the performance of the method of the invention.
  • Such equivalent genes are concomitantly absent from the samples and their abundance vary concomitantly, in the same direction and in the same proportion in the samples where they are present. This is typically the case when “gene A” is correlated to “gene B", meaning that the expression level or abundance of "gene A” is statistically correlated to the expression level of "gene B" respectively. In the context of the invention, this correlation is rather positive (meaning that when “gene A” is upregulated in a patient, then "gene” B is also upregulated in that same patient).
  • This correlation can be determined for example by a measure of association such as the Pearson's or Spearman's correlation coefficient.
  • covariance can be used for the identification of equivalent genes.
  • the equivalence of two genes is expected by the man skilled in the art to be the consequence of situations such as when two genes belong to the same genome (OJn J, Li Y, Cai Z, Li S, Zhu J, Zhang F et al., Nature, 2012), when two genes belong to the genomes of two coupled bacteria or when the product of these two genes are involved in the same metabolic and / or signaling pathway (Abubucker S, Segata N, Goll J, Schubert AM, Izard J, et al., PLoS Comput Biol, 2012).
  • covariant genes are linked with a minimum Pearson correlation of at least 0,45, more preferably 0,5, and even more preferably 0,6 to the representative genes disclosed in the present invention.
  • said equivalent gene is a covariant gene belonging to the same bacterial cluster.
  • a “gene cluster” or a “cluster” refers to a list of equivalent genes The man skilled in the art is familiar with methods that can be used to identify such clusters of equivalent genes (Qin J, Li Y, Cai Z, Li S, Zhu J, Zhang F et al., Nature, 2012).
  • Said cluster may contain several hundreds of bacterial genes, preferably covariant genes, as defined above. For simplification' purposes, only five of these covariant genes have been identified in the present application, for each cluster. In each cluster, the gene that is significantly correlated (minimum Pearson correlation > 0.7) with the most genes from the cluster has been designated as the representative gene of the cluster.
  • SEQ ID NO: 1 SEQ ID NO: 6, SEQ ID NO: 11, SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 26, SEQ ID NO: 31, SEQ ID NO: 36, SEQ ID NO: 41, SEQ ID NO: 46, SEQ ID NO: 51, SEQ ID NO: 56, SEQ ID NO: 61, SEQ ID NO: 66, SEQ ID NO: 71, SEQ ID NO: 76, SEQ ID NO: 81, SEQ ID NO: 86, SEQ ID NO: 91, SEQ ID NO: 96, SEQ ID NO: 101, SEQ ID NO: 106, SEQ ID NO: 111, SEQ ID NO: 116, SEQ ID NO: 121, SEQ ID NO: 126, SEQ ID NO: 131, SEQ ID NO: 136, SEQ ID NO: 141, SEQ ID NO: 146, and SEQ ID NO: 151. All the other genes in each cluster are "equivalent" to these representative genes. Therefore,
  • an "equivalent gene signature” is a gene signature containing, in addition to or in replacement of representative genes, equivalent genes which confer the same performance to the method of the invention. These equivalent genes have been described above.
  • the equivalent gene signature contains at least two genes that belong to two different clusters.
  • the equivalent gene signature contains at least two different genes that belong to only one cluster.
  • An equivalent gene signature may contain a mix of representative genes (SEQ ID NO: 1, 6, 11, 16, etc.) and equivalent(s) thereof, or only equivalent genes. It may also contain all the equivalent genes of a cluster. Alternatively, it may contain the arithmetic or geometric mean of the signals associated with several or all the equivalent genes of the cluster(s).
  • the gene signature may further comprise any other genes, among which, specific genes that do not significantly affect the essential characteristics of the gene signature of the invention (therefore overlapping the meaning of the term “consisting essentially of”). In contrast, by “consisting of”, it is intended to mean that no further gene is present in the gene signature which is analyzed.
  • a “reference signature” is a predetermined gene signature, obtained from a biological sample from a subject or several subjects, having known inflammation-associated disease.
  • the reference signature used for comparison with the test sample have been obtained from biological samples from subjects which have been reliably and unambiguously diagnosed (for example by means of a liver biopsy) as having an inflammatory disease and in particular a liver disease such as simple steatosis (“steatosis reference sample”) or NASH (“NASH reference sample”), and/or from biological samples from subjects which have been diagnosed for having NASH and fibrosis (“fibrosis reference sample”) and/or from biological samples from subjects which have been diagnosed for a Crohn's disease (“Crohn reference sample”) for whom the disease activity is known.
  • steatosis reference sample simple steatosis
  • NASH NASH
  • fibrosis reference sample biological samples from subjects which have been diagnosed for having NASH and fibrosis
  • Crohn reference sample Crohn's disease
  • the reference signature therefore comprises or consists of the expression and/or abundance of the bacterial genes which has (have) been determined on said reference samples.
  • these information have been obtained from a sufficient number of subjects, typically by using 96 samples of different patients for each stage of the liver disease (simple steatosis / NASH / fibrosis), using another set of 145 samples of different patients for each stage of the liver disease and using another set of 118 samples of Crohn patients with different states of the disease.
  • comparing the gene signature of a tested subject with a reference signature
  • it is meant to collect a biological sample from the tested subject, extract its genomic content, either NA or DNA, with the appropriate method, estimate the expression or relative abundance of each gene respectively, and compare either the expression and/or abundance of each gene of the signature separately with the expression and/or abundance of the same gene in the reference signature (which is not preferred), or to affect a diagnosis or prognosis outcome to the test sample using an algorithm which is calibrated based on reference samples or signatures.
  • the algorithm may issue a value, which is then compared to a predetermined reference value (e.g., via logistic regression).
  • the term "reference value” refers to a specific value or dataset that can be used to identify patients associated with an outcome class (e.g., simple steatosis, NASH or NASH-associated fibrosis, stable or instable state of Crohn's disease activity).
  • said reference or control value is obtained from the historical expression and/or abundance data for a patient or pool of patients having being diagnosed unambiguously for a define pathology.
  • This reference or control value is a predetermined value, which can take a variety of forms.
  • It can be a single cut-off value, such as a median or mean. It can be a single number, equally applicable to every patient individually, or it can vary, according to specific subpopulations of patients. This reference value can be easily determined by the skilled person with any of the above-mentioned calculation models.
  • a reagent for the determination of a gene signature designates a reagent or a set of reagents which specifically allows for the determination of said gene signature, i.e., specifically intended for the specific determination of the abundance and/or expression level of the genes comprised in the gene signature.
  • These reagents can be for example nucleic acid primers or probes that can specifically hybridize with the m NA, DNA, or cDNA included in the gene signature. They can be alternatively antibodies or enzymes specifically recognizing the proteins produced by the genes included in the gene signature.
  • This definition excludes generic reagents useful for the determination of the gene signature of any gene, such as Taq polymerase or an amplification buffer, although such reagents may also be included in a kit according to the invention.
  • a reagent e.g., a probe, a primer or an antibody
  • a reagent is "specific” for its target or “recognizes specifically” its target if it exhibits a threshold level of binding activity, and/or 2) it does not significantly cross-react with known related molecules.
  • a threshold level of binding activity e.g., a probe, a primer or an antibody
  • One skilled in the art can readily determine said binding affinity.
  • the present inventors analysed by quantitative metagenomic the gene abundance of bacterial genes on a number of stool samples that have been collected from patients for which a recent liver biopsy reading was available or whose Crohn's disease activity was monitored.
  • clusters of genes have been found to be commonly associated with benign steatosis or a stable state of Crohn disease, and 7 clusters of genes have been found to be associated with more advanced liver disease (NASH, fibrosis, cirrhosis). Furthermore, 8 clusters of genes have been found to be highly associated with NASH without fibrosis, and 2 clusters of genes have been found to be associated with NASH-associated fibrosis.
  • NASH advanced liver disease
  • fibrosis fibrosis
  • cirrhosis fibrosis, cirrhosis
  • 8 clusters of genes have been found to be highly associated with NASH without fibrosis
  • 2 clusters of genes have been found to be associated with NASH-associated fibrosis.
  • Several combinations of a minimum number of genes are therefore proposed as being predictive of benign steatosis, or of NASH with or without fibrosis or of Crohn's disease activity.
  • 4 clusters of genes have been found to be highly associated with benign steatosis
  • the method of the invention not only permits to diagnose a particular inflammatory disease stage, but also permits to prognose a positive or a negative outcome of a subject suffering from said inflammatory disease, in particular liver disease or Crohn's disease.
  • the gut microbiota is acquired during infancy (between 0-3 years old).
  • the host immune system holds a key role in the selection of a definitive core microbiota which is specific (in its composition) of each individual and remains stable over time.
  • the core microbiota stability which has been observed over the time and throughout life, is independent of dietary changes and is resilient (i.e. recovered after iatrogenic disruption). Considering this stability and resilience, the features (composition, richness, diversity) of the core microbiota are correlated with defined inflammation-induced metabolic disturbances and will be present at the onset of the pathology and throughout the evolution of the disease.
  • a fatty liver will progress to an advanced liver damage such as steatohepatitis, fibrosis, or cirrhosis, or will remain benign throughout the patient's life, by simply analyzing the gut microbiota of said patient at a point of time during the course of the disease.
  • gut microbiota holds a key role in controlling gut barrier function and in particular its permeability. Changes in gut microbiota composition lead to gut barrier function alteration promoting bacterial translocation (presence of bacteria and their components in the blood) and metabolic endotoxemia (presence of endotoxins in the blood) that initiate the development of inflammation. Therefore, inflammation-induced disturbances such as diabetes, hypertension, hypercholesterolemia, inflammatory bowel diseases and liver diseases are initially driven by impaired gut permeability triggered by changes in the gut microbiota composition (Cani P., Gut microbes, 2012).
  • a test based on gut microbiota analysis which aims to diagnose, monitor or predict evolution of a liver disease might thus be as well useful for diagnosis, monitoring or prediction of any other inflammation-associated disturbances (i.e., diabetes, hypertension, hypercholesterolemia, inflammatory bowel diseases and cardiovascular diseases).
  • any other inflammation-associated disturbances i.e., diabetes, hypertension, hypercholesterolemia, inflammatory bowel diseases and cardiovascular diseases.
  • the invention thus relates to a method for the in vitro diagnosis or prognosis of an inflammatory disease in a subject, comprising the following steps: a) determining from a biological sample of said subject a gene signature comprising or consisting of one bacterial gene, preferably of at least two bacterial genes, b) comparing the obtained gene signature with at least one reference gene signature, c) determining the phenotype of said subject from said comparison.
  • the method of the invention can also be used for predicting the outcome of a patient suffering from an inflammatory disease.
  • said inflammatory disease is chosen in the group consisting of: insulin resistance, hypercholesterolemia, impaired glucose tolerance, type 2 diabetes, hypertension, cardiovascular diseases, inflammatory bowel disease and liver disease.
  • said inflammatory disease is an inflammatory bowel disease
  • a liver disease such as benign steatosis, NASH or NASH-associated fibrosis.
  • the method of the invention can be applied to any subject, either human or animal. Yet, in a preferred embodiment, it is applied to a human patient, in particular to a human suffering from overweight, obesity, liver disease, diabetes (that is, from any metabolic disorders) and/or inflammatory bowel diseases.
  • the method of the invention is useful for monitoring human patients showing enhanced level of hepatic enzymes such as aminotransferases, alkaline phosphatase, gamma-glutamyl transferase, as well as markers of hepatocyte injuries, such as CK18, alpha macroglobulin, platelet volume, haptoglobin, Apolipoproteine Al, and bilirubin.
  • hepatic enzymes such as aminotransferases, alkaline phosphatase, gamma-glutamyl transferase, as well as markers of hepatocyte injuries, such as CK18, alpha macroglobulin, platelet volume, haptoglobin, Apolipoproteine Al, and bilirubin.
  • the method of the invention is useful for monitoring human patients showing enhanced level of inflammation markers such as platelet count, mean platelet volume, erythrocyte sedimentation rate (ES ), serum thrombopoietin, serum erythropoietin, C- reactive protein and orosomucoid (a acid glycoprotein), TNFalpha, Interleukins (notably I LI, I L2, I L6, IL8, I L10, I L15) as well as fecal markers of inflammation such as lactoferrin and calprotectin.
  • ES erythrocyte sedimentation rate
  • serum thrombopoietin serum erythropoietin
  • C- reactive protein and orosomucoid a acid glycoprotein
  • TNFalpha e.g., TNFalpha
  • Interleukins notably I LI, I L2, I L6, IL8, I L10, I L15
  • fecal markers of inflammation such as lactoferrin and calprotectin.
  • clusters of bacterial genes that are differentially abundant in the stool of patients suffering from benign steatosis, NASH and/or NASH-associated fibrosis, or in samples from Crohn patients in stable or instable state. These clusters of bacterial genes are presented in Table 1 below. Each cluster of bacterial genes is thought to be representative of a bacterial entity and contains several hundreds of bacterial genes that are present / absent altogether and in the same proportion (so-called "covariant genes"). For simplification's purpose, only five of these covariant genes have been identified in the present application, for each cluster. These five genes and all the genes belonging to the same cluster are held as "equivalent”. More precisely, as disclosed in table 1 below,
  • cluster 1 contains at least 425 genes among which the five genes SEQ ID NO:l-5 (Minimum Pearson correlation : 0.64),
  • cluster 2 contains at least 473 genes among which the five genes SEQ ID NO:6-10 (Minimum Pearson correlation: 0.72),
  • ⁇ cluster 3 contains at least 486 genes among which the five genes SEQ ID NO:ll-15 (Minimum Pearson correlation: 0.72),
  • cluster 4 contains at least 324 genes among which the five genes SEQ ID NO:16-20 (Minimum Pearson correlation: 0.7),
  • cluster 5 contains at least 515 genes among which the five genes SEQ ID NO:21-25 (Minimum Pearson correlation: 0.86),
  • cluster 6 contains at least 320 genes among which the five genes SEQ ID NO:26-30 (Minimum Pearson correlation: 0.66),
  • cluster 7 contains at least 456 genes among which the five genes SEQ ID NO:31-35 (Minimum Pearson correlation: 0.7),
  • ⁇ cluster 8 contains at least 336 genes among which the five genes SEQ ID NO:36-40 (Minimum
  • cluster 9 contains at least 509 genes among which the five genes SEQ ID NO:41-45 (Minimum Pearson correlation: 0.8),
  • cluster 10 contains at least 275 genes among which the five genes SEQ ID NO:46-50 (Minimum Pearson correlation: 0.86),
  • cluster 11 contains at least 646 genes among which the five genes SEQ ID NO:51-55 (Minimum Pearson correlation: 0.74),
  • cluster 12 contains at least 320 genes among which the five genes SEQ ID NO:56-60 (Minimum Pearson correlation: 0.86),
  • ⁇ cluster 13 contains at least 323 genes among which the five genes SEQ ID NO:61-65 (Minimum Pearson correlation 0.7),
  • cluster 14 contains at least 593 genes among which the five genes SEQ ID NO:66-70 (Minimum Pearson correlation: 0.7), • cluster 15 contains at least 283 genes among which the five genes SEQ ID NO:71-75 (Minimum Pearson correlation: 0.74),
  • cluster 16 contains at least 621 genes among which the five genes SEQ ID NO:76-80 (Minimum Pearson correlation: 0.76),
  • ⁇ cluster 17 contains at least 263 genes among which the five genes SEQ ID NO:81-85 (Minimum Pearson correlation: 0.82),
  • cluster 18 contains at least 1039 genes among which the five genes SEQ ID NO:86-90 (Minimum Pearson correlation: 0.82),
  • cluster 19 contains at least 1231 genes among which the five genes SEQ ID NO:91-95 (Minimum Pearson correlation: 0.74),
  • cluster 20 contains at least 712 genes among which the five genes SEQ ID NO:96-100 (Minimum Pearson correlation: 0.8),
  • cluster 21 contains at least 575 genes among which the five genes SEQ ID NO:101-105 (Minimum Pearson correlation: 0.88),
  • ⁇ cluster 22 contains at least 1232 genes among which the five genes SEQ ID NO:106-110 (Minimum Pearson correlation: 0.64),
  • cluster 23 contains at least 298 genes among which the five genes SEQ ID NO:lll-115 (Minimum Pearson correlation: 0.7),
  • cluster 24 contains at least 785 genes among which the five genes SEQ ID NO:116-120 (Minimum Pearson correlation: 0.76),
  • cluster 25 contains at least 780 genes among which the five genes SEQ ID NO:121-125 (Minimum Pearson correlation: 0.82),
  • cluster 26 contains at least 491 genes among which the five genes SEQ ID NO:126-130 (Minimum Pearson correlation: 0.72),
  • ⁇ cluster 27 contains at least 827 genes among which the five genes SEQ ID NO:131-135 (Minimum Pearson correlation: 0.64),
  • cluster 28 contains at least 531 genes among which the five genes SEQ ID NO:136-140 (Minimum Pearson correlation: 0.88)
  • cluster 29 contains at least 289 genes among which the five genes SEQ ID NO:141-145 (Minimum Pearson correlation: 78),
  • cluster 30 contains at least 320 genes among which the five genes SEQ ID NO:146-150 (Minimum Pearson correlation: 0.74),
  • cluster 31 contains at least 299 genes among which the five genes SEQ ID NO:151-155 (Minimum Pearson correlation: 0.66). In each cluster, the gene that is significantly correlated (Pearson correlation > 0.7) with the most genes from the cluster has been designated as the representative gene of the cluster.
  • the sequences of these representative genes are SEQ ID NO: 1, SEQ ID NO: 6, SEQ ID NO: 11, SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 26, SEQ ID NO: 31, SEQ ID NO: 36, SEQ ID NO: 41, SEQ ID NO: 46, SEQ ID NO: 51, SEQ ID NO: 56, SEQ ID NO: 61, SEQ ID NO: 66, SEQ ID NO: 71, SEQ ID NO: 76,
  • the method of the invention is highly sensitive and specific when the expression and/or the abundance of only one or two bacterial genes chosen in the above-mentioned clusters is determined and compared, directly or indirectly, to reference gene signature (see examples below). It is therefore equivalent to use a gene signature containing the representative genes (for example SEQ ID NO:l for cluster 1) or containing any of their equivalent genes (for example SEQ ID NO:2 or 3 or 4 or 5 for cluster 1).
  • the gene signature contains at least two different genes belonging to the same cluster (either a
  • the gene signature contains at least two different genes said genes belonging to at least two different clusters.
  • the method of the invention can use the gene signature of SEQ ID NO:l and SEQ ID NO:6, or of SEQ ID NO:2 and SEQ ID NO:6, or of SEQ ID NO:3 and SEQ ID NO:6, or of SEQ ID NO:3 and SEQ ID NO:6, or of SEQ ID NO:3 and SEQ ID NO:7, or of SEQ ID NO:l and SEQ ID NO:9, etc.
  • the gene signature determined in the method of the invention comprises or consists of one or at least two bacterial genes, preferably at least three, preferably at least four, preferably at least five, preferably at least six, preferably at least seven, preferably at least eight, preferably at least nine, preferably at least ten, preferably at least eleven, preferably at least twelve, preferably at least thirteen, preferably at least fourteen, preferably at least fifteen, preferably at least sixteen, preferably at least seventeen, preferably at least eighteen, preferably at least nineteen, preferably at least twenty, preferably at least twenty-one, preferably at least twenty-two, preferably at least twenty-three, preferably at least twenty-four, preferably at least twenty-five, preferably at least twenty-six, preferably at least twenty-seven, preferably at least twenty-eight, preferably at least twenty-nine, preferably at least thirty, preferably at least thirty-one bacterial genes.
  • said bacterial genes belong to the same cluster or to different clusters of genes
  • the above-mentioned bacterial genes are chosen in the group consisting of: SEQ ID NO: 1, SEQ ID NO: 6, SEQ ID NO: 11, SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 26, SEQ ID NO: 31, SEQ ID NO: 36, SEQ ID NO: 41, SEQ ID NO: 46, SEQ ID NO: 51, SEQ ID NO:
  • the gene signature determined in the method of the invention comprises or consists of an equivalent gene signature thereof.
  • the above-mentioned bacterial genes are chosen in the group consisting of: SEQ ID NO: 1, SEQ ID NO: 51, SEQ ID NO: 91, and SEQ ID NO: 151, that are highly associated with define stage of liver and bowel-related disorders.
  • the gene signature determined in the method of the invention comprises or consists of a bacterial gene chosen in the group consisting of: SEQ ID NO: 1, SEQ ID NO: 51, SEQ ID NO:
  • the gene signature determined in the method of the invention comprises or consists of an equivalent gene signature thereof.
  • said "equivalent gene signature" corresponds to a gene signature in which at least one so-called representative gene has been replaced by an equivalent thereof as defined above, said equivalent being preferably a covariant gene belonging to the same bacterial entity.
  • equivalent genes of SEQ ID NO:l are chosen in the group consisting in SEQ ID NO:2-5
  • equivalent genes of SEQ ID NO:6 are chosen in the group consisting in SEQ ID NO:7-10
  • equivalent genes of SEQ ID NO:ll are chosen in the group consisting in SEQ ID NO:
  • equivalent genes of SEQ ID NO:16 are chosen in the group consisting in SEQ ID NO:17- 20
  • equivalent genes of SEQ ID NO:21 are chosen in the group consisting in SEQ ID NO:22-25
  • equivalent genes of SEQ ID NO:26 are chosen in the group consisting in SEQ ID NO:27-30
  • equivalent genes of SEQ ID NO:31 are chosen in the group consisting in SEQ ID NO:32-35
  • equivalent genes of SEQ ID NO:36 are chosen in the group consisting in SEQ ID NO:37-40
  • equivalent genes of SEQ ID NO:41 are chosen in the group consisting in SEQ ID NO:42-45
  • equivalent genes of SEQ ID NO:46 are chosen in the group consisting in SEQ ID NO:47-50
  • equivalent genes of SEQ ID NO:51 are chosen in the group consisting in SEQ ID NO:52-55
  • equivalent genes of SEQ ID NO:56 are chosen in the group consisting in SEQ ID NO:57-60
  • equivalent genes of SEQ ID NO:61 are chosen in the group consisting
  • the method of the invention uses a gene signature comprising or consisting of the bacterial gene of SEQ ID NO:l or equivalent gene(s) thereof (for example chosen among SEQ ID NO:2-5) belonging to cluster 1.
  • the method of the invention uses a gene signature comprising or consisting of the bacterial gene whose sequence is SEQ ID NO: 1, or an equivalent gene signature thereof.
  • This equivalent gene signature preferably contains one or more gene(s) chosen from SEQ ID NO:2 to 5.
  • This bacterial gene is preferably used to prognose or diagnose liver-disease or Crohn disease according to the methods of the invention.
  • the method of the invention uses a gene signature comprising or consisting of the bacterial gene of SEQ ID NO:51 or equivalent gene(s) thereof (for example chosen among SEQ ID NO:52-55) belonging to cluster 11.
  • the method of the invention uses a gene signature comprising or consisting of the bacterial gene whose sequence is SEQ ID NO: 51, or an equivalent gene signature thereof.
  • This equivalent gene signature preferably contains one or more gene(s) chosen from SEQ ID NO:52 to 55.
  • This bacterial gene is preferably used to prognose or diagnose liver-disease according to the methods of the invention.
  • the method of the invention uses a gene signature comprising or consisting of the bacterial gene of SEQ ID NO:91 or equivalent gene(s) thereof (for example chosen among SEQ ID NO:92-95) belonging to cluster 19.
  • the method of the invention uses a gene signature comprising or consisting of the bacterial gene whose sequence is SEQ ID NO: 91, or an equivalent gene signature thereof.
  • This equivalent gene signature preferably contains one or more gene(s) chosen from SEQ ID NO:92 to 95.
  • This bacterial gene is preferably used to prognose or diagnose liver-disease or Crohn disease according to the methods of the invention.
  • the method of the invention uses a gene signature comprising or consisting of the bacterial gene of SEQ ID NO:151 or equivalent gene(s) thereof (for example chosen among SEQ ID NO:152-155) belonging to cluster 31.
  • the method of the invention uses a gene signature comprising or consisting of the bacterial gene whose sequence is SEQ ID NO: 151, or an equivalent gene signature thereof.
  • This equivalent gene signature preferably contains one or more gene(s) chosen from SEQ ID NO:152 to 155.
  • This bacterial gene is preferably used to prognose or diagnose liver-disease or Crohn disease according to the methods of the invention.
  • step a) of the method of the invention it is possible in step a) of the method of the invention to use a gene signature comprising or consisting of at least one gene of each of the clusters identified by the inventors.
  • a gene signature comprising or consisting of all the so-called "representative" genes identified by the inventors, optionally along with equivalent(s) thereof.
  • a gene signature taking into account the signals of all the so-called “representative” genes along with their equivalents genes.
  • a gene signature taking into account the arithmetic or geometric mean of the signals associated with several or all the equivalent genes of the cluster(s) (example lb and 2b).
  • a “biological sample” may be any sample that may be taken from a subject, such as a serum sample, a plasma sample, a urine sample, a blood sample, a stool sample, a lymph sample, or a biopsy. Such a sample must allow for the determination of the gene signature of the invention.
  • Preferred biological samples for the determination of the gene signature in the method of the invention include stool sample and gut biopsy (gut biopsy via colonoscopy is notably less invasive than a liver biopsy).
  • the biological sample used in the method of the invention is a stool sample.
  • a sample may be obtained by a completely harmless collection from the patient and thus allows for a non-invasive diagnosis of an inflammatory disease such as a liver disease or an inflammatory-bowel disease.
  • the DNA can be extracted from said sample for example by using the extraction protocol described in Godon JJ. et al, Appl. Environ. Microbiol. 1997. Other protocols can nevertheless be used and are well-known.
  • the bacterial DNA and the host DNA do not need to be physically separated for subsequent metagenomic analysis.
  • the determination of the presence of an inflammatory disease such as in certain Crohn's patients or patients with a liver disease is carried out thanks to the comparison of the obtained gene signature with at least one reference signature, as mentioned in step (b) of the method of the invention.
  • the comparison of a tested subject gene signature with said reference signature which permits diagnosis or prediction of the tested subject's clinical status and evolution based on his/her abundance or expression profile, is preferably performed by applying an algorithm on the gene signals measured in the tested sample. This calculation can be done by those skilled in the art using statistical models or machine learning technologies.
  • the PLS (Partial Least Square) regression is particularly relevant to give prediction in the case of small reference samples.
  • the comparison may also be performed using Recursive Partitioning, Support Vector Machines (SVM), linear regression or derivatives thereof (such as the generalized linear model abbreviated as GLM, including logistic regression), Linear Discriminant Analysis (LDA, including Diagonal Linear Discriminant Analysis (DLDA)), Diagonal quadratic discriminant analysis (DQDA), Random Forests, k-NN (Nearest Neighbour) or PAM (Predictive Analysis of Microarrays) algorithms. Cox models may also be used. Centroid models using various types of distances may also be used.
  • SVM Support Vector Machines
  • LDA Linear Discriminant Analysis
  • DQDA Diagonal quadratic discriminant analysis
  • Random Forests Random Forests
  • k-NN Nearest Neighbour
  • PAM Predictive Analysis of Microarrays
  • the reference samples mentioned above are usually used to select and calibrate the optimal statistical algorithm that best separates patients suffering from each stage of an inflammatory disease such as liver disease or inflammatory-bowel disease.
  • the best separation is generally the one that misclassifies as few samples as possible and that has the best chance to perform comparably well on a different dataset.
  • linear regression For a binary outcome such as benign / malignant diagnosis, linear regression or a generalized linear model (abbreviated as GLM), including logistic regression, may be used.
  • GLM generalized linear model
  • Logistic regression is based on the determination of a logistic regression function:
  • x x to x N are the expression or abundance values of the N genes in the signature, ⁇ 0 is the intercept, and ⁇ ⁇ to ⁇ ⁇ are the regression coefficients.
  • the values of the intercept and of the regression coefficients are determined based on a group of the reference samples as defined above.
  • the user associates good or bad diagnosis (e.g., a diagnosis of simple steatosis or NASH, or of stable or instable state of Crohn disease, respectively) or prognosis to define values and a particular threshold value (hereafter called "reference value”) is identified.
  • a test gene signature can then be classified as having a good or bad diagnosis (e.g., a diagnosis of simple steatosis or NASH, or of stable or instable state of Crohn disease, respectively) or prognosis (benign or inflammatory steatosis).
  • a good or bad diagnosis e.g., a diagnosis of simple steatosis or NASH, or of stable or instable state of Crohn disease, respectively
  • prognosis benign or inflammatory steatosis
  • Other types of generalized linear models than logistic regression may also be used. These approaches are well known to people skilled in the art.
  • an algorithm (which may be selected from linear regression or derivatives thereof such as generalized linear models (GLM, including logistic regression), nearest neighbour (k-NN), decision trees, support vector machines (SVM), neural networks, linear discriminant analyses (LDA), Random forests, or Predictive Analysis of Microarrays (PAM)) is calibrated based on a group of reference samples (preferably including several reference signatures associated to benign steatosis and several reference signatures associated to NASH and NASH-associated fibrosis) and then applied to the test sample.
  • a patient will be classified as good (or bad) diagnosis / prognosis based on how all the genes in his signature compare to all the genes from the reference signature(s).
  • the method of the invention permits to determine whether a subject is suffering from a liver disease, and, in particular, from benign steatosis, NASH or NASH- associated fibrosis.
  • the present invention thus relates to a method for the in vitro diagnosis and/or prognosis of a liver disease, comprising the following steps: a) determining from a biological sample of a subject a gene signature comprising or consisting of one bacterial gene, preferably of at least two bacterial genes, b) comparing the obtained gene signature with at least one reference gene signature, c) determining the phenotype of said subject from said comparison.
  • said liver disease is chosen in the group consisting of: steatosis, non alcoholic steatohepatitis, liver fibrosis, cirrhosis, liver failure, and liver cancer.
  • the method of the present invention can be used for the diagnosis or prognosis of particular stages of a liver disease.
  • the method of the present invention can be used for the (good) diagnosis or prognosis of benign steatosis or for the (bad) diagnosis or prognosis of steatohepatitis.
  • the method of the invention comprises the steps of: a) determining from a biological sample of a subject a gene signature comprising or consisting of one or at least two bacterial genes chosen in the group consisting of: SEQ ID NO: 1, SEQ ID NO: 6, SEQ ID NO: 11, SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 26, SEQ ID NO: 31, SEQ ID NO: 36, SEQ ID NO: 41, SEQ ID NO: 46, SEQ ID NO: 51, SEQ ID NO: 56, SEQ ID NO: 61, SEQ ID NO: 66, SEQ ID NO: 71, SEQ ID NO: 76, SEQ ID NO: 81, SEQ ID NO: 86, SEQ ID NO: 91, SEQ ID NO: 96, SEQ ID NO: 101 or an equivalent gene signature thereof, b) comparing the obtained gene signature with at least one reference signature, c) diagnosing from said comparison if the said subject has a benign steatosis or a steatohe
  • a benign steatosis is considered as a positive result, while steatohepatitis is considered as a negative result (considering that the patient is suffering from or will suffer from steatohepatitis).
  • the present inventors have indeed demonstrated that a combination of one or more bacterial genes chosen in the group consisting of: SEQ ID NO: 1, SEQ ID NO: 6, SEQ ID NO: 11, SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 26, SEQ ID NO: 31, SEQ ID NO: 36, SEQ ID NO: 41, SEQ ID NO: 46, SEQ ID NO: 51, SEQ ID NO: 56, SEQ ID NO: 61, SEQ ID NO: 66, SEQ ID NO: 71, SEQ ID NO: 76, SEQ ID NO: 81, SEQ ID NO: 86, SEQ ID NO: 91, SEQ ID NO: 96, SEQ ID NO: 101 or of equivalent genes thereof, enables to discriminate efficiently between subjects suffering from steatohepatitis (that is, suffering from NASH with or without fibrosis) or more advanced liver disease (cirrhosis, liver cancer) and subjects having benign steatosis (cf. example 1 below).
  • benign steatosis or steatohepatitis is diagnosed by determining the gene signature consisting of the four representative genes: SEQ ID NO: 1, SEQ ID NO:81, SEQ ID NO:56 and SEQ ID NO:96, which has been shown to be highly specific and relatively sensitive (AUC:0.83, sn: 0.62; sp: 0.9; PPV: 0.72; NPV:0.85), or a gene signature consisting of the nine representative genes: SEQ ID NO: 1, SEQ ID NO:16, SEQ ID NO:41, SEQ ID NO: 71, SEQ ID NO:81, SEQ ID NO:21, SEQ ID NO: 46, SEQ ID NO:91, and SEQ ID NO:96, which has been shown to be highly specific and sensitive (AUC:0.86, sn: 0.66; sp: 0.9; PPV: 0.73; NPV:0.86), or a gene signature consisting of the ten representative genes: SEQ ID NO: 1, SEQ ID NO:
  • benign steatosis or steatohepatitis is diagnosed by determining a gene signature consisting of all the genes of the six clusters 1, 5, 17, 10, 12 and 20 (see table 1 below), which has been shown to be highly specific and sensitive (AUC:0.81, sn: 0.48; sp: 0.94; PPV: 0.78; NPV:0.81), or a gene signature consisting of all the genes of the 10 clusters 2, 5, 8, 12, 13, 15, 16, 17, 18, and 21, which has been shown to be highly specific and sensitive (AUC:0.8, sn: 0.52; sp: 0.9; PPV: 0.68; NPV:0.81).
  • benign steatosis or steatohepatitis is diagnosed by determining a gene signature consisting of at least one gene of each of the two clusters 1 and 31 (see table 1 below for the correspondence with the targeted sequences) which has been shown to not sensitive but very specific (AUC:0.64, sn: 0.29; sp: 0.9; PPV: 0.48; NPV:0.8), or a gene signature consisting of at least one gene of each of the four clusters 1, 16, 13 and 14 which has been shown to be highly specific and sensitive (AUC:0.76, sn: 0.59; sp: 0.87; PPV: 0.65; NPV:0.83) or a gene signature consisting of at least one gene of each of the 5 clusters 12, 5, 10, 18 and 19 (AUC:0.7, sn: 0.41; sp: 0.94; PPV: 0.75; NPV:0.79) which has been shown to be highly specific and sensitive or a gene signature consisting of at least one gene of each of the
  • the method of the present invention can be used for the diagnosis or prognosis of subjects suffering from a steatohepatitis with fibrosis once they have been diagnosed for steatohepatitis, in particular by means of the steps a) to c) above.
  • the method of the invention further comprises the steps of: d) Determining in said biological sample a gene signature comprising or consisting of one or at least two bacterial genes chosen in the group consisting of: SEQ ID NO: 106, SEQ ID NO: 111, SEQ
  • fibrosis-associated steatohepatitis is diagnosed by determining the gene signature consisting of the seven representative genes: SEQ ID NO: 106, SEQ ID NO:lll, SEQ ID NO:116, SEQ ID NO:121; SEQ ID NO:131, SEQ ID NO:136 and SEQ ID NO:151, which has been shown to be highly specific and sensitive (AUC:0.83, sn: 0.76; sp: 0.82; PPV: 0.81; NPV:0.78), or a gene signature consisting of the eight representative genes: SEQ ID NO: 106, SEQ ID NO:lll, SEQ ID NO:116, SEQ ID NO: 121, SEQ ID NO:126, SEQ ID NO:131, SEQ ID NO: 136, and SEQ ID NO:151, which has been shown to be highly specific and sensitive (AUC:0.81, sn: 0.82; sp: 0.79; PPV: 0.79; NPV:0.82).
  • fibrosis-associated steatohepatitis is diagnosed by determining a gene signature consisting of all the genes of the six clusters 22, 23, 25, 27, 28 and 31 (see table 1 below for the correspondence with the targeted sequences), which has been shown to be highly specific and sensitive (AUC:0.85, sn: 0.74; sp: 0.85; PPV: 0.83; NPV:0.76), or a gene signature consisting of all the genes of the seven clusters 22, 23, 24, 25, 27, 28, and 31, which has been shown to be highly specific and sensitive (AUC:0.85, sn: 0.88; sp: 0.7; PPV: 0.75; NPV:0.85).
  • the method of the present invention can be used for the diagnosis or prognosis of particular states of Crohn patients.
  • the method of the present invention can be used for the diagnosis or prognosis of a Crohn patient in a stable state or for the diagnosis or prognosis of a Crohn patient in an instable state.
  • the method of the invention comprises the steps of: a) determining from a biological sample of a subject a gene signature comprising or consisting of one or at least two bacterial genes chosen in the group consisting of: SEQ ID NO: 1, SEQ ID NO: 6, SEQ ID NO: 11, SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 26, SEQ ID NO: 31, SEQ ID NO: 36, SEQ ID NO: 41, SEQ ID NO: 46, SEQ ID NO: 51, SEQ ID NO: 56, SEQ ID NO: 61, SEQ ID NO: 66, SEQ ID NO: 71, SEQ ID NO: 76, SEQ ID NO: 81, SEQ ID NO: 86, SEQ ID NO: 91, SEQ ID NO: 96, SEQ ID NO: 101 or an equivalent gene signature thereof, b) comparing the obtained gene signature with at least one reference signature, c) diagnosing from said comparison if the said subject has a Crohn disease in a stable or instable state.
  • a "Crohn patient in a stable state” or “stable Crohn disease” is considered as a positive result, while a "Crohn patient in an instable state” or “an instable Crohn disease” is considered as a negative result.
  • the present inventors have indeed demonstrated that one or more bacterial genes chosen in the group consisting of: SEQ ID NO: 1, SEQ ID NO: 6, SEQ ID NO: 11, SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 26, SEQ ID NO: 31, SEQ ID NO: 36, SEQ ID NO: 41, SEQ ID NO: 46, SEQ ID NO: 51, SEQ ID NO: 56, SEQ ID NO: 61, SEQ ID NO: 66, SEQ ID NO: 71, SEQ ID NO: 76, SEQ ID NO: 81, SEQ ID NO: 86, SEQ ID NO: 91, SEQ ID NO: 96, SEQ ID NO: 101 or of equivalent genes thereof, enables to discriminate efficiently between subjects suffering from stable Crohn disease or instable Crohn disease (cf. example 4 below).
  • the Crohn disease is prognosed or diagnosed by determining a gene signature consisting of at least one gene of each of the 5 clusters 3, 11, 17, 10, and 18 (see table 1 below for the correspondence with the targeted sequences), which has been shown to be highly specific and sensitive (AUC:0.73, sn: 0.4; sp: 0.99; PPV: 0.89, NPV:0.89), or a gene signature consisting of at least one gene of each of the six clusters 2, 7, 11, 15, 17, and 18, which has been shown to be highly specific and sensitive (AUC:0.74, sn: 0.4; sp: 0.99; PPV: 0.89; NPV:0.89) or a gene signature consisting of at least one gene of each of the six clusters 3, 11, 13, 15, 17, and 18, which has been shown to be highly specific and sensitive (AUC:0.74, sn: 0.4; sp:
  • the gene signature may be determined by any technology known by a man skilled in the art.
  • each gene expression or abundance may be measured at the genomic and/or nucleic and/or proteic level.
  • the gene signature is determined by measuring the amount of the DNA copies of each gene.
  • the gene signature is determined by measuring the amount of nucleic acid transcripts and/or protein produced by each of the genes.
  • the gene signature of the subject in step a) and d) is determined by using methods of gene abundance profiling based on hybridization analysis of polynucleotides, sequencing of polynucleotides, and/or proteomics.
  • the amount of DNA copies of each gene can be measured by any technology known by a man skilled in the art.
  • antibodies may be employed that can recognize sequence-specific duplexes, including DNA duplexes or DNA-protein duplexes.
  • Representative methods for sequencing-based analysis include chain-termination methods, shotgun sequencing methods, de novo sequencing, next generation sequencing methods (including Massively Parallel Signature Sequencing (MPSS), Polony sequencing, 454 pyrosequencing, lllumina (Solexa) sequencing, SOLiD sequencing, Ion semiconductor sequencing, DNA nanoball sequencing, Helioscope single molecule sequencing, Single molecule real time (SMRT) sequencing, RNAP sequencing, Nanopore DNA sequencing, Sequencing by hybridization and Microfluidic Sanger sequencing).
  • MPSS Massively Parallel Signature Sequencing
  • Polony sequencing Polony sequencing
  • 454 pyrosequencing 454 pyrosequencing
  • lllumina (Solexa) sequencing SOLiD sequencing
  • Ion semiconductor sequencing DNA nanoball sequencing
  • Helioscope single molecule sequencing Single molecule real time (SMRT) sequencing
  • RNAP sequencing Single molecule real time
  • the amount of protein produced by the genes can be measured by any technology known by a man skilled in the art.
  • the measure may be carried out by using a protein microarray, in situ fluorescent hybridization (FISH) or any technologies well-known in the art.
  • FISH in situ fluorescent hybridization
  • the gene signature in step a) and d) of the method of the invention is determined by measuring the relative abundance of said bacterial genes.
  • the relative abundance of a gene is assessed for example by measuring the total number of the copies of said gene and the total amount of bacterial genes present in the tested sample and by making a ratio between these two amounts.
  • it is possible to measure the number of gene copies for example by sequencing the DNA extracted from faecal samples using high throughput sequencing technologies (Next Generation Sequencing or NGS), mapping / aligning the short reads obtained on a non-redundant reference catalogue and counting the number of reads mapped to a single reference sequence from the catalogue.
  • NGS Next Generation Sequencing
  • Normalizing the number of reads mapped over the length of the genes and normalizing the gene counts over the total amount of bacterial genes are the two preferred options to normalize the data.
  • the diagnosis and/or prognosis methods of the invention can be used for designing a treatment for a subject suffering from a inflammatory disease such as a liver disease or inflammatory bowel disease.
  • the methods of the invention comprise the additional step of designing a treatment for the subject, said treatment being adapted to the particular pathology which has been diagnosed (by the method of the invention).
  • an adapted treatment can be a pharmacological treatment chosen in the group consisting of: antidiabetic drugs, such as (but not limited to), metformin, biguanides, thiazolidinediones, sulfonylureas, meglitinides, alpha-glucosidase inhibitors, incretin mimetics (including glucagon-like peptide analogs and agonists, gastric inhibitory peptide analogs, dipeptidyl Peptidase-4 Inhibitors, amylin analogues), TGR5 activators, GPR119 ligands, Glucokinase activators, agonist of zinc transporters, ILlbeta inhibitors, inhibitors of thioredoxin- interacting protein; as well as lifestyle interventions, such as a broad spectrum of diets of different caloric restriction intensities and macronutrient composition (low carbohydrate,
  • an adapted treatment can be a pharmacological treatment chosen in the group consisting of: antidiabetics drugs, such as (but not limited to) metformin, biguanides, thiazolidinediones, sulfonylureas, meglitinides, alpha-glucosidase inhibitors, incretin mimetics (including glucagon-like peptide analogs and agonists, gastric inhibitory peptide analogs, dipeptidyl Peptidase-4 Inhibitors, amylin analogues), TGR5 activators, GPR119 ligands, Glucokinase activators, agonist of zinc transporters, ILlbeta inhibitors, inhibitors of thioredoxin- interacting protein, enteric lipase inhibitors; as well as peripheral cannabinoid receptor blockers or agonists, as well as anti
  • antidiabetics drugs such as (but not limited to) metformin, biguanides, thiazol
  • an adapted treatment can be a pharmacological treatment chosen in the group consisting of: antidiabetics drugs, such as (but not limited to) metformin, biguanides, thiazolidinediones, sulfonylureas, meglitinides, alpha-glucosidase inhibitors, incretin mimetics (including glucagon-like peptide analogs and agonists, gastric inhibitory peptide analogs, dipeptidyl Peptidase-4 Inhibitors, amylin analogues), TGR5 activators, GPR119 ligands, Glucokinase activators, agonist of zinc transporters, ILlbeta inhibitors, inhibitors of thioredoxin-interacting protein, enteric lipase inhibitors; as well as peripheral cannabinoid receptor blockers or agonists, as well
  • antidiabetics drugs such as (but not limited to) metformin, biguanides, thiazolidinedi
  • an adapted treatment can be a pharmacological treatment chosen in the group consisting of: antidiabetics drugs, such as (but not limited to) metformin, biguanides, thiazolidinediones, sulfonylureas, meglitinides, alpha-glucosidase inhibitors, incretin mimetics (including glucagon-like peptide analogs and agonists, gastric inhibitory peptide analogs, dipeptidyl Peptidase-4 Inhibitors, amylin analogues), TGR5 activators, GPR119 ligands, Glucokinase activators, agonist of zinc transporters, ILlbeta inhibitors, inhibitors of thioredoxin-interacting protein, enteric lipase inhibitors; as well as peripheral cannabinoid receptor blockers or agonists, as well as
  • antidiabetics drugs such as (but not limited to) metformin, biguanides, thiazolidined
  • an adapted treatment can be a pharmacological treatment chosen in the group consisting of: azathioprine, mesalamine, abatacept, adalimumab, anakinra, certolizumab, etanercept, golimumab, infliximab, rituximab, tocilizumab, natalizumab, corticosteroids, cyclosporine, methotrexate, tacrolimus, Anti-JAK (tofacitinib), anti-integrins (Vedolizumab, rhuMAb Beta7, MAdCAM-1 Antagonist), or Anti IL12/IL23 (Ustekinumab, ABT874).
  • the invention encompasses a method for treating a subject suffering from an inflammatory disease, comprising the following steps: i) diagnosing and / or prognosing an inflammatory disease such as a type 2 diabetes, hypercholesterolemia, hypertension, inflammatory bowel disease (e.g., Crohn disease) or liver disease in a subject according to the method of the invention, and ii) treating said subject with an appropriate treatment, said appropriate treatment being chosen in those classically attributed by the practitioner once said inflammatory disease is diagnosed.
  • an inflammatory disease such as a type 2 diabetes, hypercholesterolemia, hypertension, inflammatory bowel disease (e.g., Crohn disease) or liver disease
  • said appropriate treatments can be chosen in the group consisting of : antidiabetics drugs, such as (but not limited to) metformin, biguanides, thiazolidinediones, sulfonylureas, meglitinides, alpha-glucosidase inhibitors, incretin mimetics (including glucagon-like peptide analogs and agonists, gastric inhibitory peptide analogs, dipeptidyl Peptidase-4 Inhibitors, amylin analogues), TGR5 activators, GPR119 ligands, Glucokinase activators, agonist of zinc transporters, ILlbeta inhibitors, inhibitors of thioredoxin-interacting protein, enteric lipase inhibitors; as well as peripheral cannabinoid receptor blockers or agonists, as well as antioxydants, such as (but not limited to) pentoxifylline vitamin E and vitamin D, as well as caspase inhibitors, P
  • the invention encompasses a method for managing a subject suffering from an inflammatory disease, comprising the following steps: i) diagnosing and / or prognosing an inflammatory disease such as a type 2 diabetes, hypercholesterolemia, hypertension, inflammatory bowel disease (e.g., Crohn disease) or liver disease in a subject according to the method of the invention, and ii) taking care of said subject with an appropriate treatment, said appropriate treatment being chosen in those classically attributed by the practitioner once said inflammatory disease is diagnosed.
  • an inflammatory disease such as a type 2 diabetes, hypercholesterolemia, hypertension, inflammatory bowel disease (e.g., Crohn disease) or liver disease
  • said appropriate treatments are preferably lifestyle interventions, for example diets of different caloric restriction intensities and macronutrient composition (low carbohydrate, low fat, saturated fat diets); and/or bariatric surgery procedures including (but not limited to) gastric band, bilio-intestinal bypass, gastric bypass, and gastric sleeve surgery.
  • lifestyle interventions for example diets of different caloric restriction intensities and macronutrient composition (low carbohydrate, low fat, saturated fat diets); and/or bariatric surgery procedures including (but not limited to) gastric band, bilio-intestinal bypass, gastric bypass, and gastric sleeve surgery.
  • the invention encompasses a method for treating a subject suffering from a liver disease, comprising the following steps: i) diagnosing and / or prognosing benign steatosis, steatohepatitis, or fibrosis-associated steatohepatitis in a subject according to the method of the invention, and ii) treating said subject with an appropriate treatment, said appropriate treatment being chosen in those classically attributed by the practitioner once said stage of liver disease is diagnosed.
  • said appropriate treatments can be chosen in the group consisting of: antidiabetics drugs, such as (but not limited to) metformin, biguanides, thiazolidinediones, sulfonylureas, meglitinides, alpha-glucosidase inhibitors, incretin mimetics (including glucagon-like peptide analogs and agonists, gastric inhibitory peptide analogs, dipeptidyl Peptidase-4 Inhibitors, amylin analogues), TGR5 activators, GPR119 ligands, Glucokinase activators, agonist of zinc transporters, ILlbeta inhibitors, inhibitors of thioredoxin-interacting protein, enteric lipase inhibitors; as well as peripheral cannabinoid receptor blockers or agonists, as well as antioxydants, such as (but not limited to) pentoxifylline, vitamin E and vitamin D, as well as caspase inhibitors, P
  • the invention encompasses a method for managing a subject suffering from a liver disease, comprising the following steps: i) diagnosing and / or prognosing benign steatosis, steatohepatitis, or fibrosis-associated steatohepatitis in a subject according to the method of the invention, and ii) taking care of said subject with an appropriate treatment, said appropriate treatment being chosen in those classically attributed by the practitioner once said stage of liver disease is diagnosed.
  • said appropriate treatments are preferably lifestyle interventions, for example diets of different caloric restriction intensities and macronutrient composition (low carbohydrate, low fat, saturated fat diets); and/or bariatric surgery procedures including (but not limited to) gastric band, bilio-intestinal bypass, gastric bypass, and gastric sleeve surgery.
  • lifestyle interventions for example diets of different caloric restriction intensities and macronutrient composition (low carbohydrate, low fat, saturated fat diets); and/or bariatric surgery procedures including (but not limited to) gastric band, bilio-intestinal bypass, gastric bypass, and gastric sleeve surgery.
  • the invention encompasses a method for treating a subject suffering from an inflammatory bowel disease such as a Crohn disease, comprising the following steps: i) diagnosing and / or prognosing the state of the patient suffering from an inflammatory bowel disease in a subject according to the method of the invention, and ii) treating said subject with an appropriate treatment, said appropriate treatment being chosen in those classically attributed by the practitioner once said state of the inflammatory bowel disease is diagnosed.
  • an inflammatory bowel disease such as a Crohn disease
  • an adapted treatment can be a pharmacological treatment chosen in the group consisting of: azathioprine, mesalamine, abatacept, adalimumab, anakinra, certolizumab, etanercept, golimumab, infliximab, rituximab, tocilizumab, natalizumab, corticosteroids, cyclosporine, methotrexate, tacrolimus, Anti-JAK (tofacitinib), anti-integrins (Vedolizumab, rhuMAb Beta7, MAdCAM-1 Antagonist), or Anti IL12/IL23 (Ustekinumab, ABT874).
  • the present invention further concerns a kit for the in vitro diagnosis and/or prognosis of an inflammatory disease such as a liver disease or a Crohn disease according to the method of the invention, comprising at least one reagent for the determination of a gene signature comprising at least one or two bacterial genes chosen in the group consisting of: SEQ ID NO: 1, SEQ ID NO: 6, SEQ ID NO: 11, SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 26, SEQ ID NO: 31, SEQ ID NO: 36, SEQ ID NO: 41, SEQ ID NO: 46, SEQ ID NO: 51, SEQ ID NO: 56, SEQ ID NO: 61, SEQ ID NO: 66, SEQ ID NO: 71, SEQ ID NO: 76, SEQ ID NO: 81, SEQ ID NO: 86, SEQ ID NO: 91, SEQ ID NO: 96, SEQ ID NO: 101, SEQ ID NO: 106, SEQ ID NO: 111, SEQ ID NO: 116
  • Said kit may comprise additional reagents (e.g., primers, probes or antibodies) specific for additional genes or gene products of one or more reference gene(s).
  • Reference genes herein designate genes having an ubiquitous level of expression and/or abundance across bacteria, that can be used to normalize the gene levels for the signature.
  • Said kit may also contain instructions for the determination of the presence or absence of an inflammatory disease such as a liver disease or an inflammatory bowel disease.
  • the reagents included in the kit of the invention are specific for SEQ ID NO: 1, SEQ ID NO:81, SEQ ID NO:56 and SEQ ID NO:96; for SEQ ID NO: 1, SEQ ID NO:16, SEQ ID NO:41, SEQ ID NO: 71, SEQ ID NO:81, SEQ ID NO:21, SEQ ID NO: 46, SEQ ID NO:91, and SEQ ID NO:96; for SEQ ID NO: 1, SEQ ID NO:6, SEQ ID NO:ll, SEQ ID NO:21, SEQ ID NO: 31, SEQ ID NO:41, SEQ ID NO:51, SEQ ID NO: 61, SEQ ID NO:76, and SEQ ID NO:96; for all the genes of the six clusters 1, 5,
  • kits for all the genes of the 10 clusters 2, 5, 8, 12, 13, 15, 16, 17, 18, and 21 if the kit is intended to diagnose or prognose benign steatosis.
  • these reagents are specific for SEQ ID NO :1, SEQ ID NO :91, SEQ ID NO :51 and/or SEQ ID NO :151.
  • the reagents included in the kit of the invention are specific for: SEQ ID NO: 106, SEQ ID NO:lll, SEQ ID NO:116, SEQ ID NO:121; SEQ ID NO:131, SEQ ID NO:136 and SEQ ID NO:151; for SEQ ID NO: 106, SEQ ID NO:lll, SEQ ID NO:116, SEQ ID NO: 121, SEQ ID NO:126, SEQ ID NO:131, SEQ ID NO: 136, and SEQ ID NO:151; for all the genes of the six clusters 22, 23, 25, 27, 28 and 31 ; or for all the genes of the seven clusters 22, 23, 24, 25, 27, 28, and 31, if the kit is intended to diagnose or prognose fibrosis-associated steatohepatitis.
  • the kit of the invention is dedicated to the in vitro diagnosis and/or prognosis of an inflammatory disease such as liver diseases or inflammatory bowel diseases.
  • an inflammatory disease such as liver diseases or inflammatory bowel diseases.
  • the reagents in the kit of the invention essentially consist of reagents for determining the abundance and/or expression level of the particular genes included in the gene signature, optionally with one or more housekeeping gene(s), and thus comprise a minimum of reagents for determining the expression and/or abundance of genes other than those mentioned in the gene signature and housekeeping genes.
  • the invention thus relates to a method for the in vitro diagnosis or prognosis of an inflammatory disease in a subject, said method using the kit of the invention, which is defined above.
  • said method comprises the following steps: a) determining from a biological sample of said subject a gene signature comprising or consisting of one bacterial gene, preferably of at least two bacterial genes, thereby using the kit of the invention as defined above, b) comparing the obtained gene signature with at least one reference gene signature, c) determining the phenotype of said subject from said comparison.
  • the said method permits to determine whether a subject is suffering or will suffer from a liver disease, and, in particular, from benign steatosis, NASH or NASH- associated fibrosis, in the conditions defined above.
  • the said method permits to determine whether a subject has a Crohn disease in a stable or instable state, in the conditions defined above.
  • the instructions for the determination of the presence or absence of a Crohn / liver disease phenotype preferably include at least one reference signature, or at least one reference sample for obtaining a reference signature.
  • at least one reference signature is obtained from a steatosis reference sample.
  • at least one reference signature is obtained from a NASH reference sample.
  • at least one reference signature is obtained from a fibrosis reference sample.
  • at least one reference signature is obtained from a Crohn-stable reference sample.
  • at least one reference signature is obtained from a Crohn instable reference sample. More preferably, the determination of the diagnosis of the Crohn / liver disease is carried out by comparison with these reference signatures as described above.
  • the present invention also related to a nucleic acid microarray comprising or consisting of nucleic acids specific for one or at least two bacterial genes chosen in the group consisting of: SEQ ID NO: 1, SEQ ID NO: 6, SEQ ID NO: 11, SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 26, SEQ ID NO: 31, SEQ ID NO: 36, SEQ ID NO: 41, SEQ ID NO: 46, SEQ ID NO: 51, SEQ ID NO: 56, SEQ ID NO: 61, SEQ ID NO: 66, SEQ ID NO: 71, SEQ ID NO: 76, SEQ ID NO: 81, SEQ ID NO: 86, SEQ ID NO: 91, SEQ ID NO: 96, SEQ ID NO: 101, SEQ ID NO: 106, SEQ ID NO: 111, SEQ ID NO: 116, SEQ ID NO: 121, SEQ ID NO: 126, SEQ ID NO: 131, SEQ ID NO: 136, SEQ ID NO
  • these microarrays comprise or consist of nucleic acids specific for at least one bacterial gene chosen in the group consisting of: for SEQ ID NO :1, SEQ ID NO :91, SEQ ID NO :51 and SEQ ID NO :151.
  • these microarrays comprise or consist of nucleic acids specific at least one gene of each of the clusters 1 and 31, of each of the clusters 1, 16, 13 and 14, or of each of the clusters 3, 16, 13, 15, 16, 11, 14, 7 and 4 (see table 1 below for the correspondence with the targeted sequences). They can be used for example to prognose or diagnose liver disease in patients suffering thereof.
  • these microarrays comprise or consist of nucleic acids specific at least one gene of each of the clusters 3, 11, 17 and 10, of each of the clusters 2, 7, 11, 15, 17 and 18, or of each of the clusters 3, 11, 13, 15, 17 and 18, or of each of the clusters 3, 11, 12, 14, 17 and 18 (see table 1 below for the correspondence with the targeted sequences). They can be used for example to prognose or diagnose evolution of Crohn disease in patients suffering thereof.
  • a "nucleic microarray” consists of different nucleic acid probes that are attached to a substrate, which can be a microchip, a glass slide or a microsphere-sized bead.
  • a microchip may be constituted of polymers, plastics, resins, polysaccharides, silica or silica-based materials, carbon, metals, inorganic glasses, or nitrocellulose.
  • Probes can be nucleic acids such as cDNAs ("cDNA microarray”) or oligonucleotides (“oligonucleotide microarray”), and the oligonucleotides may be about 25 to about 60 base pairs or less in length.
  • the nucleic acid microarray of the invention is an oligonucleotide microarray carrying oligonucleotides that can specifically hybridize with one or at least two bacterial genes chosen in the group consisting of: SEQ ID NO: 1, SEQ ID NO: 6, SEQ ID NO: 11, SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 26, SEQ ID NO: 31, SEQ ID NO: 36, SEQ ID NO: 41, SEQ ID NO: 46, SEQ ID NO: 51, SEQ ID NO: 56, SEQ ID NO: 61, SEQ ID NO: 66, SEQ ID NO: 71, SEQ ID NO: 76, SEQ ID NO: 81, SEQ ID NO: 86, SEQ ID NO: 91, SEQ ID NO: 96, SEQ ID NO: 101, SEQ ID NO: 106,
  • the oligonucleotides are about 50 bases in length.
  • nucleic acid microarray of the invention encompasses the microarrays specific for the equivalent gene signature as defined above.
  • said nucleic acid microarray comprises or consists of nucleic acids specific for at least SEQ ID NO: 1, SEQ ID NO:81, SEQ ID NO:56 and SEQ ID NO:96; for SEQ ID NO: 1, SEQ ID NO:16, SEQ ID NO:41, SEQ ID NO: 71, SEQ ID NO:81, SEQ ID NO:21, SEQ ID NO: 46, SEQ ID NO:91, and SEQ ID NO:96; for SEQ ID NO: 1, SEQ ID NO:6, SEQ ID NO:ll, SEQ ID NO:21, SEQ ID NO: 31, SEQ ID NO:41, SEQ ID NO:51, SEQ ID NO: 61, SEQ ID NO:76, and SEQ ID NO:96; for all the genes of the six clusters 1, 5, 17, 10, 12 and 20; or for all the genes of the 10 clusters 2, 5, 8, 12, 13, 15, 16, 17, 18,
  • said nucleic acid microarray comprises or consists of nucleic acids specific for at least one bacterial gene chosen in the group consisting of: for SEQ ID NO :1, SEQ ID NO :91, SEQ ID NO :51 and SEQ ID NO :151.
  • said nucleic acid microarray comprises or consists of nucleic acids specific at least one gene of each of the clusters 1 and 31, of each of the clusters 1, 16, 13 and 14, or of each of the clusters 3, 16, 13, 15, 16, 11, 14, 7 and 4 (see table 1 below for the correspondence with the targeted sequences). They can be used for example to prognose or diagnose liver disease in patients suffering thereof.
  • said nucleic acid microarray comprises or consists of nucleic acids specific at least one gene of each of the clusters 3, 11, 17 and 10, of each of the clusters 2, 7, 11, 15, 17 and 18, or of each of the clusters 3, 11, 13, 15, 17 and 18, or of each of the clusters 3, 11, 12, 14, 17 and 18 (see table 1 below for the correspondence with the targeted sequences). They can be used for example to prognose or diagnose evolution of Crohn disease in patients suffering thereof.
  • said microarray comprises or consists of nucleic acids specific for at least: SEQ ID NO: 106, SEQ ID NO:lll, SEQ ID NO:116, SEQ ID NO:121; SEQ ID NO:131, SEQ ID NO:136 and SEQ ID NO:151; for SEQ ID NO: 106, SEQ ID NO:lll, SEQ ID NO:116, SEQ ID NO: 121, SEQ ID NO:126, SEQ ID NO:131, SEQ ID NO: 136, and SEQ ID NO:151; for all the genes of the six clusters 22, 23, 25,
  • Said nucleic acid microarray may comprise additional nucleic acids specific for additional genes and optionally one or more reference gene(s), but preferably consists of a maximum of 500, 400, 300, 200 preferably 100, 90, 80, 70 more preferably 60, 50, 45, 40, 35, 30, 25, 20, 15, 10, or even less (for instance 9, 8, 7, 6, 5, 4, 3, 2 or 1) distinct nucleic acids.
  • said sample is labelled, contacted with the nucleic acid microarray of the invention in hybridization conditions, leading to the formation of complexes between target nucleic acids that are complementary to probe sequences attached to the microarray surface. The presence of labelled hybridized complexes on the nucleic acid microarray is then detected.
  • Many variants of the microarray hybridization technology are available to the man skilled in the art.
  • Suitable microarray oligonucleotides specific for any gene of SEQ ID NO: 1 to 155 may be designed, based on the genomic sequence of each gene, using any method of microarray oligonucleotide design known in the art.
  • any available software developed for the design of microarray oligonucleotides may be used, such as, for instance, the OligoArray software
  • the invention thus relates to a method for the in vitro diagnosis or prognosis of an inflammatory disease in a subject, said method using the microarray of the invention, which is defined above.
  • said method comprises the following steps: a) determining from a biological sample of said subject a gene signature comprising or consisting of one bacterial gene, preferably of at least two bacterial genes, thereby using the microarray of the invention as defined above, b) comparing the obtained gene signature with at least one reference gene signature, c) determining the phenotype of said subject from said comparison.
  • the said method permits to determine whether a subject is suffering or will suffer from a liver disease or an inflammatory bowel disease, and, in particular, from benign steatosis, NASH or NASH-associated fibrosis, in the conditions defined above.
  • a clustering approach was used, using the co-variance principle.
  • a two-step hierarchical graph clustering was applied to 435 samples from the MetaHIT consortium mapped to the 3.3 million gene catalogue.
  • This approach consists on a parametric partitioning method, using the DAPC algorithm.
  • the optimal number of cluster (i.e k) in a gene set the 3 pam 2 function was used to estimate the optimal silhouette widths3.
  • DAPC method was applied using the 3 adegenet 2 library in R programming environment. The minimal number of principal components including at least 90% of total variability was used to cluster the genes.
  • This second step allowed grouping all genes into subunits, which corresponded to the identified clusters.
  • the relative abundance of the predetermined clusters of genes was obtained by averaging the abundance of the genes in the cluster. Only the clusters with more than 500 items were used, as it corresponds to the minimal size of known bacteria.
  • the log-transformed abundance profiles of the clusters of genes have been tested against the phenotypes (either benign steatosis versus NASH or NASH + fibrosis, or NASH versus NASH + fibrosis) using Kolmogorov-Smirnov and Wilcoxon non-parametric tests.
  • the clusters that pass either test p-value threshold: 0.05
  • the sub-clusters that contain more than 250 elements were tested using Kolmogorov-Smirnov and Wilcoxon tests. Only the sub-cluster that most significantly passes the test was selected.
  • SEQIDNO:81 SEQ ID NO :82-85 bacteroides Benign steatosis (1731_5)
  • SEQIDNO:86 SEQ ID NO :87-90 bacteroides NASH or NASH fibrosis (1731_14)
  • SEQIDNO:91 SEQIDNO:92-95 Escherichia NASH or NASH fibrosis (6069_2_2)
  • table 1 indicates the correspondence between: the cluster numbers and the targeted sequences listed in the enclosed listing
  • NPV true and false positive results, NPV, PPV, specificity and sensitivity are defined and calculated as follows:
  • NPV Negative Predictive Value
  • AUC Area Under the Curve
  • N PV, PPV, specificity and sensitivity are defined and calculated as follows:
  • NPV Negative Predictive Value
  • enterotype 1 is known to derive energy primarily from carbohydrates and proteins through fermentation. These enterotypes shape the microbes hosted in the gut and consequently the presence/absence/abundance of the different species.
  • the marker of interest for the phenotype may be dependent of such arrangements of the microbiota.
  • NASH1 patients The NASH1 group of patients (“NASH1 patients”) A single-centre cross-sectional study has been conducted from November 2011 to January 2012 to determine the metagenotypes in stool samples of 96 adult subjects who have had a liver biopsy prior to enrollment. Exclusion criteria were : antibiotic therapy within previous 6 weeks, regular intake of probiotics during last 2 weeks, colonoscopy within previous 6 months, previous intestinal (bariatric) surgery, alcohol consumption >20 g/d (w)/ >30 g/d (m), identifia ble cause of liver disease (viral, autoimmune, genetic, toxic, drug-induced). Each subject received a kit (FecotainerTM + AnaeroGenTM) for collecting faeces himself at home and a 30 € fee for participation. The stools were kept at 4°C and transported within 36h.
  • kit FecotainerTM + AnaeroGenTM
  • NASH2 patients The NASH2 group of patients ("NASH2 patients")
  • NASH2 patients were recruited with the same inclusion criteria as patients from NASHl.
  • the recruitment was extended to several new centers (Amiens, Angers, Berne, Bordeaux, Nice and another center from Paris) to complement the recruitment from the original center.
  • the collection method was slightly modified for practical reasons: one stool sample only was collected and stored in a fixative solution during transport at ambient temperature.
  • Crohn patients 19 patients were recruited in St Louis and St Antoine hospitals in Paris. Several samples were collected for each patient, summing up to 118 samples collected.
  • Crohn disease evolves in time and the status of the patient may change at each sampling point.
  • the criteria chosen for the description of the state of the disease for each sample is related to stability in time. At the moment of the sampling, the patient is considered stable if :
  • the mgs 10764_1_2 (SEQ ID NO: 1-5 and cluster 1) is of high interest on NASHl, NASH2 and Crohn patients
  • - "-10" is an artificial value introduced when the mgs is not detected
  • Metformin is an anti diabetic treatment that is known to modify the gut microbiota
  • Threshold approach Using an automatic procedure to determine threshold separating low and high abundance, figures 2D), 2E) and 2F) have been obtained (the number of patients for whom the information is available in indicated between brackets).
  • - "-10" is an artificial value introduced when the mgs is not detected
  • Metformin is an anti diabetic treatment that is known to modify the gut microbiota
  • the mgs 6069_2_2 (SEQ ID NO: 91 - 95 - cluster 19) is of high interest on NASHl, NASH2 and Crohn patients
  • figures 3 D, E, and F have been obtained (the number of patients for whom the information is avalailable in indicated between brackets). N.B.
  • - "-10" is an artificial value introduced when the mgs is not detected
  • Metformin is an anti diabetic treatment that is known to modify the gut microbiota
  • Samples where the mgs 6069_2_2 is abundant tend to be less healthy, i.e. in NASH cohorts (NASHl, NASH2), patients are more prone to have the advanced state of the disease, i.e. NASH, and not Simple Steatosis, and in Crohn, patients are more prone to be instable.
  • NASH NASH cohorts
  • NASH Simple Steatosis
  • Crohn patients are more prone to be instable.
  • NASH1 Number of Simple Steatosis / Number of NASH
  • Thresholds were determined for each mgs of interest, so that patient samples could be split into a subset of interest that contains samples with low (alternatively, high) relative abundance of the mgs and another subset that contains the other samples (the probability of enrichment at the different thresholds is evaluated using the binomial distribution).
  • PPV and NPV Positive and Negative Predictive Values estimate the number of good predictions made when a test is positive.
  • PPV or NPV estimates the ratio of the number of good predictions when the relative abundance of the mgs is above (resp. below) the pre-determined threshold. The higher the PPV or NPV and the larger the subsets of selected samples, the more useful is the predictor.
  • the subset of interest was enriched in patients with one phenotype (for NASH cohort : Benign or NASH, for Crohn : stable or instable), in which case the relative abundance of the mgs could be used to identify patients with a specific phenotype (note that the other patient samples may not be associated with any status).
  • the mgs 6063_6_3 (SEQ ID NO:51-55 + cluster 11) is of intermediate interest (NASHl + NASH2)
  • the results of the global approach for this mgs are disclosed on figures 4 and 4B (the number of patients for whom the information is available in indicated between brackets).
  • figures 4 C and D have been obtained (the number of patients for whom the information is avalailable in indicated between brackets) :
  • NASH 1 6063_6 low/high versus NASH status
  • the mgs numbers referred to in the following table are related to the clusters disclosed the correspondance table 1.
  • Cluster 17 Cluster 17 + cluster 11 + cluster 15+ cluster 2 + cluster 7 + cluster 18
  • Cluster 3 Cluster 17 + cluster 16 + cluster 11 + cluster 14 + cluster 18 + cluster 12
  • a simple combination of as little as two clusters of genes provides tests with significant predictive power (AUC > 0.7).
  • AUC > 0.7 The more clusters are combined, the better the performance of the test.
  • Other more sophisticated algorithms could be used to improve the performance of the test.
  • tests can be tuned with various levels of complexity and various performance outcomes by adjusting the number of clusters of genes combined and the threshold used, such as tests with high detection capability for patients with any of the phenotypes (benign steatosis or NASH or NASH + fibrosis) or balanced test with good and balanced performance.

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CN201380054047.XA CN104769132B (zh) 2012-10-17 2013-10-17 肝脏相关的炎性疾病的基因标记
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MX2015004844A MX2015004844A (es) 2012-10-17 2013-10-17 Firmas geneticas de trastornos inflamatorios que se relacionan con el higado.
DK13779214.9T DK2909334T3 (da) 2012-10-17 2013-10-17 Gensignaturer af inflammatoriske lidelser, som er relateret til leveren og Crohns sygdom
BR112015008621-7A BR112015008621A2 (pt) 2012-10-17 2013-10-17 Métodos e kit de diagnóstico e/ou prognóstico in vitro microconjunto de ácidos nucleicos.
IN3796DEN2015 IN2015DN03796A (de) 2012-10-17 2013-10-17
ES13779214T ES2821383T3 (es) 2012-10-17 2013-10-17 Firmas genéticas de trastornos inflamatorios relacionados con el hígado y la enfermedad de Crohn
EP13779214.9A EP2909334B1 (de) 2012-10-17 2013-10-17 Gensignaturen entzündlicher erkrankungen im zusammenhang mit der leber und mit morbus crohn
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3640644A4 (de) * 2017-06-13 2021-01-27 Beijing Ditan Hospital, Capital Medical University Zielmarker gp73 zum nachweis von steatohepatitis und nachweisverfahren
US11284640B2 (en) 2017-02-14 2022-03-29 University Of Southern California Fasting mimicking diet
US11810650B2 (en) 2017-04-03 2023-11-07 Gusto Global, Llc Rational design of microbial-based biotherapeutics

Families Citing this family (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10039777B2 (en) 2012-03-20 2018-08-07 Neuro-Lm Sas Methods and pharmaceutical compositions of the treatment of autistic syndrome disorders
EP4249053A3 (de) 2016-03-04 2024-06-19 The Regents of The University of California Mikrobielles konsortium und verwendungen davon
JP2019517783A (ja) * 2016-04-20 2019-06-27 ヒューマン ロンジヴィティ，インコーポレイテッド 肝疾患を検出するためのマイクロバイオーム（ｍｉｃｒｏｂｉｏｍｅ）プロファイルの使用
CA3024272A1 (en) * 2016-05-11 2017-11-16 University Of Southern California Fasting mimicking diet (fmd) as an immunoregulatory treatment for gastrointestinal autoimmune/inflammatory diseases.
EP3773645A4 (de) 2018-04-10 2021-11-24 Siolta Therapeutics, Inc. Mikrobielle konsortien
CN108504739A (zh) * 2018-05-15 2018-09-07 浙江大学 一种用于肝癌早期诊断的生物标志物及其应用
EP3899015A1 (de) * 2018-12-19 2021-10-27 Astrazeneca AB Biomarker für die pnpla3-expression
JP2022523564A (ja) 2019-03-04 2022-04-25 アイオーカレンツ， インコーポレイテッド 機械学習を使用するデータ圧縮および通信
CA3153884A1 (en) 2019-10-07 2021-04-15 Nikole KIMES Therapeutic pharmaceutical compositions
CN111884792B (zh) * 2020-06-30 2021-07-09 深圳市永达电子信息股份有限公司 基于忆阻器混沌序列的本征态网络电路信号制备系统和方法
US11688507B2 (en) 2020-12-29 2023-06-27 Kpn Innovations, Llc. Systems and methods for generating a metabolic dysfunction nourishment program

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013036290A1 (en) * 2011-09-09 2013-03-14 Yale University Compositions and methods for assessing and treating inflammatory diseases and disorders

Family Cites Families (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6582908B2 (en) * 1990-12-06 2003-06-24 Affymetrix, Inc. Oligonucleotides
US6610836B1 (en) * 1999-01-29 2003-08-26 Genome Therapeutics Corporation Nucleic acid amino acid sequences relating to Klebsiella pneumoniae for diagnostics and therapeutics
JP4852211B2 (ja) * 2000-03-21 2012-01-11 メルク アンド カンパニー インコーポレイテッド 原核生物における必須遺伝子の同定
EP1227152A1 (de) * 2001-01-30 2002-07-31 Société des Produits Nestlé S.A. Bakterienstamm und Genom des Bifidobacteriums
WO2003053220A2 (en) * 2001-12-17 2003-07-03 Corixa Corporation Compositions and methods for the therapy and diagnosis of inflammatory bowel disease
US8119365B2 (en) * 2002-01-23 2012-02-21 Wisconsin Alumni Research Foundation Insertion sequence-free bacteria
WO2004092365A1 (ja) * 2003-04-13 2004-10-28 Kyushu Tlo Company Limited 肝障害関連遺伝子群の抽出選択法およびそれを用いた肝障害もしくは肝機能評価・診断方法
US7860656B2 (en) * 2005-02-03 2010-12-28 Assistance Publique-Hopitaux De Paris (Ap-Hp) Diagnosis method of hepatic steatosis using biochemical markers
SI2351772T1 (sl) * 2005-02-18 2016-11-30 Glaxosmithkline Biologicals Sa Proteini in nukleinske kisline iz Escherichia coli povezane z meningitisom/sepso
FR2893136A1 (fr) * 2005-11-10 2007-05-11 Sanofi Aventis Sa Procedes de diagnostic de maladies hepatiques et de criblage de molecules pour le traitement de ces maladies
US20110165568A1 (en) * 2009-12-31 2011-07-07 Life Technologies Corporation Sequences of e.coli 055:h7 genome
AU2011223049B2 (en) * 2010-03-01 2015-06-18 Institut National De La Recherche Agronomique Method of diagnostic of inflammatory bowel diseases
JP5757032B2 (ja) * 2010-04-05 2015-07-29 学校法人東京医科大学 ｍｉＲＮＡを利用した慢性肝疾患の線維化の検査方法
JP2012125215A (ja) * 2010-12-17 2012-07-05 Osaka City Univ 肝線維症の存在及び／又は肝線維症の重症度の判定方法、判定マーカー、判定用キット、肝線維症の治療の効果予測方法、効果予測マーカー、並びに効果予測用キット
WO2012105590A1 (ja) * 2011-02-01 2012-08-09 アステラス製薬株式会社 非アルコール性脂肪肝炎の鑑別マーカー及び当該マーカーを指標とした非アルコール性脂肪肝炎の診断方法
WO2012159023A2 (en) * 2011-05-19 2012-11-22 Virginia Commonwealth University Gut microflora as biomarkers for the prognosis of cirrhosis and brain dysfunction
US20140377278A1 (en) * 2012-01-10 2014-12-25 Yale University Compositions and Methods for Assessing and Treating Inflammatory Diseases and Disorders
ES2683826T3 (es) 2012-10-17 2018-09-28 Institute National De La Recherche Agronomique Determinación de la diversidad bacteriana intestinal reducida
US20150284779A1 (en) 2012-10-17 2015-10-08 Institut National De La Recherche Agronomique Determination of a tendency to gain weight
MX2015004809A (es) 2012-10-17 2015-11-16 Agronomique Inst Nat Rech Pronostico del impacto de la dieta sobre las co-morbilidades relacionadas con la obesidad.
US9459650B2 (en) 2014-03-17 2016-10-04 Qualcomm Incorporated Clock pulse generator for multi-phase signaling

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013036290A1 (en) * 2011-09-09 2013-03-14 Yale University Compositions and methods for assessing and treating inflammatory diseases and disorders

Non-Patent Citations (13)

* Cited by examiner, † Cited by third party
Title
ABU AL-SOUD ET AL: "DNA of Helicobacter spp. and common gut bacteria in primary liver carcinoma", DIGESTIVE AND LIVER DISEASE, W.B. SAUNDERS, GB, vol. 40, no. 2, 20 December 2007 (2007-12-20), pages 126 - 131, XP022412855, ISSN: 1590-8658 *
ANTYA RODOLPHE ET AL: "Liver fibrogenesis and metabolic factors", CLINICS AND RESEARCH IN HEPATOLOGY AND GASTROENTEROLOGY, vol. 35, no. Suppl. 1, June 2011 (2011-06-01), pages S10 - S20, XP008159949 *
BAJAJ JASMOHAN S ET AL: "Linkage of gut microbiome with cognition in hepatic encephalopathy", AMERICAN JOURNAL OF PHYSIOLOGY - GASTROINTESTINAL AND LIVER PHYSIOLOGY, vol. 302, no. 1, January 2012 (2012-01-01), pages G168 - G175, XP002692034 *
BERGHEIM I ET AL: "Antibiotics protect against fructose-induced hepatic lipid accumulation in mice: Role of endotoxin", JOURNAL OF HEPATOLOGY, ELSEVIER, AMSTERDAM, NL, vol. 48, no. 6, 1 June 2008 (2008-06-01), pages 983 - 992, XP022648567, ISSN: 0168-8278, [retrieved on 20080314], DOI: 10.1016/J.JHEP.2008.01.035 *
DUMAS M-E ET AL: "Metabolic profiling reveals a contribution of gut microbiota to fatty liver phenotype in insulin-resistant mice", PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES, NATIONAL ACADEMY OF SCIENCES, US, vol. 103, no. 33, 15 August 2006 (2006-08-15), pages 12511 - 12516, XP003022530, ISSN: 0027-8424, DOI: 10.1073/PNAS.0601056103 *
ERAN ELINAV ET AL: "NLRP6 Inflammasome Regulates Colonic Microbial Ecology and Risk for Colitis", CELL, CELL PRESS, US, vol. 145, no. 5, 22 April 2011 (2011-04-22), pages 745 - 757, XP028221175, ISSN: 0092-8674, [retrieved on 20110502], DOI: 10.1016/J.CELL.2011.04.022 *
HENAO-MEJIA JORGE ET AL: "Inflammasome-mediated dysbiosis regulates progression of NAFLD and obesity", NATURE (LONDON), vol. 482, no. 7384, February 2012 (2012-02-01), pages 179, XP002692032 *
IACONO ANNA ET AL: "Probiotics as an emerging therapeutic strategy to treat NAFLD: focus on molecular and biochemical mechanisms", JOURNAL OF NUTRITIONAL BIOCHEMISTRY, vol. 22, no. 8, August 2011 (2011-08-01), pages 699 - 711, XP002692036 *
LI DING-YOU ET AL: "Nonalcoholic Fatty liver disease: for better or worse, blame the gut microbiota?", JPEN. JOURNAL OF PARENTERAL AND ENTERAL NUTRITION 2013 NOV-DEC, vol. 37, no. 6, November 2013 (2013-11-01), pages 787 - 793, XP008165856, ISSN: 0148-6071 *
MUSSO GIOVANNI ET AL: "Gut microbiota as a regulator of energy homeostasis and ectopic fat deposition: mechanisms and implications for metabolic disorders", CURRENT OPINION IN LIPIDOLOGY, vol. 21, no. 1, February 2010 (2010-02-01), pages 76 - 83, XP008159948, ISSN: 0957-9672 *
PARNELL JILL A ET AL: "The potential role of prebiotic fibre for treatment and management of non-alcoholic fatty liver disease and associated obesity and insulin resistance", LIVER INTERNATIONAL, vol. 32, no. 5, May 2012 (2012-05-01), pages 701 - 711, XP002692037 *
SPENCER MELANIE D ET AL: "Association Between Composition of the Human Gastrointestinal Microbiome and Development of Fatty Liver With Choline Deficiency", GASTROENTEROLOGY, vol. 140, no. 3, March 2011 (2011-03-01), pages 976 - 986, XP002692033 *
WANG B ET AL: "MICROBIOMIC PROFILES DELINEATE POTENTIAL ROLE FOR GUT MICROBIOTA IN NONALCOHOLIC FATTY LIVER DISEASE", JOURNAL OF HEPATOLOGY, vol. 56, no. Suppl. 2, April 2012 (2012-04-01), & 47TH ANNUAL MEETING OF THE EUROPEAN-ASSOCIATION-FOR-THE-STUDY-OF-THE-LIVER (EASL); BARCELONA, SPAIN; APRIL 18 -22, 2012, pages S513, XP008159946, ISSN: 0168-8278 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11284640B2 (en) 2017-02-14 2022-03-29 University Of Southern California Fasting mimicking diet
US11810650B2 (en) 2017-04-03 2023-11-07 Gusto Global, Llc Rational design of microbial-based biotherapeutics
EP3640644A4 (de) * 2017-06-13 2021-01-27 Beijing Ditan Hospital, Capital Medical University Zielmarker gp73 zum nachweis von steatohepatitis und nachweisverfahren

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